worth the energy cost for the robot. The creator must be aware of and weigh these two options to build an efficient robot. References Artificial Intelligence: A Modern Approach by Stuart Russell, Peter Norvig An Introduction To Least Commitment Planning by Daniel Weld Kambhampati, S., Knoblock, C.A., Yang, Q. (1994). Planning as Refinement Search: A Unified Framework for Evaluating Design Tradeoffs in Partial-Order Planning. Elsevier Science. Poole, D., Mackworth, A. (2010). Partial-Order Planning in Artificial Intelligence Foundations of Computational Agents. Cambridge University Press. Dyer, C. R. “Partial-Order Planning (Chapter 11).”(2003) CS 540. University of Wisconsin-Madison. Madison, Wisconsin. Barrett, A., and Weld, D. (1993). Partial-Order Planning: Evaluating Possible Efficiency Gains. University of Washington: Department of Computer Science and Engineering. Notes. Simmons, Reid. (2001). “Planning, Execution & Learning 1. Partial Order Planning.” Carnegie Mellon University. Pittsburgh. Notes. http://pdf.aminer.org/000/744/302/partial_order_planning_evaluating_possible_efficiency_gains.pdf http://pdf.aminer.org/000/037/660/decomposition_and_causality_in_partial_order_planning.pdf http://dl.acm.org/citation.cfm?id=1867345 http://arxiv.org/pdf/1106.0249.pdf http://www.grastien.net/ban/teaching/06-planning4.pdf